4.7 Article

Expression of ferroptosis-related gene correlates with immune microenvironment and predicts prognosis in gastric cancer

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SCIENTIFIC REPORTS
卷 12, 期 1, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41598-022-12800-6

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资金

  1. National Natural Science Foundation of China [81673918]
  2. 2019 Construction Project of Evidence-based Capacity for Traditional Chinese Medicine in state administration of traditional Chinese medicine [2019XZZX-ZL003]
  3. Open Program of the Third Phase of the Program of Traditional Chinese Medicine (TCM) Advantageous Subjects [ZYX03KF020]
  4. Science and Technology Project of Jiangsu Provincial Administration of Traditional Chinese Medicine [ZD201803]

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This study explores the role of ferroptosis-related genes in gastric cancer development and establishes a prognostic signature for predicting patient outcomes. The results indicate a connection between ferroptosis, immune cell infiltration, and lipid metabolism, which can aid in determining immunotherapy strategies for gastric cancer patients.
The study is to explore the role of ferroptosis-related genes (FRGs) in the occurrence and development of gastric cancer (GC), and to construct a new prognosis signature to predict the prognosis in GC. Clinical information and corresponding RNA data of GC patients were downloaded from TCGA and GEO databases. Consensus clustering was performed to identify new molecular subgroups. ESTIMATE, CIBERSORT, McpCounter and TIMER algorithm were used to analyze the infiltration of immune cells in two molecular subgroups. LASSO algorithm and multivariate Cox analysis were used to construct a prognostic risk signature. Functional analysis was conducted to elucidate the underlying mechanisms. Finally, the FRPGs were verified by Quantitative Real-Time PCR. We obtained 16 FRGs and divided GC patients into two subgroups by consistent clustering. Cluster C1 with a higher abundance of immune cell infiltration but lower probability in response to immunotherapy, it was reasonable to speculate that Cluster C1 was in accordance with the immune rejection type. Functional analysis showed that the biological process of DEGs in training cohort mainly included immune globulin, and human immune response mediated by circulating immune globulin. GSEA analysis showed that compared with Cluster C2, Cluster C1 showed lower expression in lipid metabolism. The nomogram combined with risk signature and clinical features can accurately predict the prognosis of GC patients. We identified two molecular subtypes, Clusters C1 and C2. In Cluster C1, patients with poor prognosis present with a hyperimmune status and low lipid metabolism, and we speculate that Cluster C1 was in accordance with the immune rejection type. The risk model based on FRPGs can accurately predict the prognosis of GC. These results indicated that ferroptosis is associated with TIME, and deserved considerable attention in determining immunotherapy treatment strategy for GC patients.

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